TLR Tolerance Reduces IFN-Alpha Production Despite Plasmacytoid Dendritic Cell Expansion and Anti-Nuclear Antibodies in NZB Bicongenic Mice
Bibliographic record
Abstract
Genetic loci on New Zealand Black (NZB) chromosomes 1 and 13 play a significant role in the development of lupus-like autoimmune disease. We have previously shown that C57BL/6 (B6) congenic mice with homozygous NZB chromosome 1 (B6.NZBc1) or 13 (B6.NZBc13) intervals develop anti-nuclear antibodies and mild glomerulonephritis (GN), together with increased T and B cell activation. Here, we produced B6.NZBc1c13 bicongenic mice with both intervals, and demonstrate several novel phenotypes including: marked plasmacytoid and myeloid dendritic cell expansion, and elevated IgA production. Despite these changes, only minor increases in anti-nuclear antibody production were seen, and the severity of GN was reduced as compared to B6.NZBc1 mice. Although bicongenic mice had increased levels of baff and tnf-α mRNA in their spleens, the levels of IFN-α-induced gene expression were reduced. Splenocytes from bicongenic mice also demonstrated reduced secretion of IFN-α following TLR stimulation in vitro. This reduction was not due to inhibition by TNF-α and IL-10, or regulation by other cellular populations. Because pDC in bicongenic mice are chronically exposed to nuclear antigen-containing immune complexes in vivo, we examined whether repeated stimulation of mouse pDC with TLR ligands leads to impaired IFN-α production, a phenomenon termed TLR tolerance. Bone marrow pDC from both B6 and bicongenic mice demonstrated markedly inhibited secretion of IFN-α following repeated stimulation with a TLR9 ligand. Our findings suggest that the expansion of pDC and production of anti-nuclear antibodies need not be associated with increased IFN-α production and severe kidney disease, revealing additional complexity in the regulation of autoimmunity in systemic lupus erythematosus.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".